抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

We have developed a simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s). In this procedure, recombination requires the phage lambda Red recombinase, which is synthesized under the control of an inducible promoter on an easily curable, low copy number plasmid. To demonstrate the utility of this approach, we generated PCR products by using primers with 36- to 50-nt extensions that are homologous to regions adjacent to the gene to be inactivated and template plasmids carrying antibiotic resistance genes that are flanked by FRT (FLP recognition target) sites. By using the respective PCR products, we made 13 different disruptions of chromosomal genes. Mutants of the arcB, cyaA, lacZYA, ompR-envZ, phnR, pstB, pstCA, pstS, pstSCAB-phoU, recA, and torSTRCAD genes or operons were isolated as antibiotic-resistant colonies after the introduction into bacteria carrying a Red expression plasmid of synthetic (PCR-generated) DNA. The resistance genes were then eliminated by using a helper plasmid encoding the FLP recombinase which is also easily curable. This procedure should be widely useful, especially in genome analysis of E. coli and other bacteria because the procedure can be done in wild-type cells.

/pdf/one-step-inactivation-of-chromosomal-genes-in-escherichia-25avsrekpc.pdf

One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

Biosensors. Fundamentals and Applications. : A.P.F. Turner, I. Karube and G.S. Wilson, Oxford University Press, Oxford, 1987, ISBN 0-19-854724-2, xvi + 770 pp., £60.00.

http://www.biochemsoctrans.org/content/ppbiost/14/5/882.2.full.pdf

The glucose phosphotransferase system as the major site of growth inhibition of Clostridium pasteurianum in media of high solute content

The rapid detection of COVID-19 uses genotypic testing for the presence of SARS-Cov-2 virus in nasopharyngeal swabs, but it can have a poor sensitivity. A rapid, host-based physiological test that indicated whether the individual was infected or not would be highly desirable. Coagulaopathies are a common accompaniment to COVID-19, especially micro-clots within the lungs. We show here that microclots can be detected in the native plasma of COVID-19 patient, without the addition of any clotting agent, and in particular that such clots are amyloid in nature as judged by a standard fluorogenic stain. This provides a rapid and convenient test with 100% sensitivity (P<0.0001), and is consistent with the recognition that the early detection and prevention of such clotting can have an important role in therapy.

Funding: Medical Research Council of South Africa (MRC) (Self-Initiated Research Program: A0X331) supported this collaboration. DBK funding Novo Nordisk Foundation (grant NNF10CC1016517).

Declaration of Interests: The authors declare that they have no competing interests.

Ethics Approval Statement: Ethical approval for blood collection and analysis of the patients with COVID-19, T2DM and healthy individuals, was given by the Health Research Ethics Committee (HREC) of Stellenbosch University (reference number: 9521). This laboratory study was carried out in strict adherence to the International Declaration of Helsinki, South African Guidelines for Good Clinical Practice and the South African Medical Research Council (SAMRC), Ethical Guidelines for research. Oral consent was obtained from all participants prior to any sample collection.

Prevalence of Readily Detected Amyloid Blood Clots in ‘Unclotted’ COVID-19 Plasma

NF-κB oscillations were suggested by Hoffmann et al from electro-mobility shift assays (EMSA) in population studies of IκBα-/- embryonic fibroblasts and simulated in a computational model. NF-κB oscillations were also observed by Nelson et al at the single cell level. The Hoffmann model gave a fairly good pre- diction of Nelson et al oscillatory experimental data using fluorescent proteins. A common comment on the source of oscillations is the existence of negative feedback loops. Just from the point of mathematics, we can set up a simple system containing a negative feedback loop that possesses oscillating behaviour resembling the ones observed in the experiments like Fonslet et al did. However, different models with similar structures can have dramatically different dynam- ical behaviour. In order to understand biological mechanisms, it is necessary to work on those real models that are based on experimental data even though models may be very large. In this paper, we are able to analyze the dynamical properties of Hoffmann’s large computational model (containing 24 variables and 64 parameters) by using computational and analytical methods and give an explanation of the source of oscillations. We find that the computational model can be treated as a fast-slow system where the level of total IκB Kinase (IKK) is treated as a slow variable. If we consider the limit in which the level of total IKK does not change at all, then we can take the level of total IKK as a parameter. Since the total NF-κB is conserved in the model, we can also view the total NF-κB as a parameter. If the actual variation of IKK is sufficiently slow, then orbits in the true system trace attractors in the reduced model. We find that for some range of the level of NF-κB, the reduced system experiences Hopf bifurcation twice while varying the level of total IKK. The damped oscillations observed in the computational system come from the existence of stable limit cycles and stable spirals in the reduced system family.

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Oscillations in the NF-kB signalling pathway.

Guengerich, F. P. (1978) J. Bioi. Chern. 253, 7931-7939 Kahl, G. F., Zimmer, B., Galinsky, T., Jonen, H. G. & Kahl, R. (1977) in Microsomes and Drug Oxidations (Ullrich, V., Roots, 1., Hildebrandt, A., Estabrook, R. W. & Conney, A. H., eds.), pp. 551-558, Pergamon Press, Oxford Lowry, 0. H., Rosebrough, N. J., Farr, A. L. & Randall, R. G. (1951) J. Bioi. Chern. 193, 265-276 Mailman, R. B., Tate, L. G., Muse, K. E., Coons, L. B. & Hodgson, E. (1975) Chem.-Biol. Interact. 10, 215-228 McPherson, F., Bridges, J. W. & Parke, D. V. (1974) Nature (London) 252,488-489 Parke, D. V. (1975) in Enzyme Induction (Parke, D. V., ed.), pp. 207-271, Plenum Press, London Stier, A. (1976) Biochem. Pharmacal. 25, 109-113 Ullrich, V. (1969) Hoppe-Seyler's Z. Physiol. Chern. 350, 357-365 Yang, C. S. & Strickhart, F. S. (1974) Biochem. Pharmacal. 23, 3129-3138

Douglas B. Kell

Papers

Biosensors. Fundamentals and Applications. : A.P.F. Turner, I. Karube and G.S. Wilson, Oxford University Press, Oxford, 1987, ISBN 0-19-854724-2, xvi + 770 pp., £60.00.

The glucose phosphotransferase system as the major site of growth inhibition of Clostridium pasteurianum in media of high solute content

Prevalence of Readily Detected Amyloid Blood Clots in ‘Unclotted’ COVID-19 Plasma

Oscillations in the NF-kB signalling pathway.

The generation of a membrane potential by a fermentative bacterium [proceedings].